Christine Tuleau-Malot

Statistics and Probability · 2009–2015

A researcher in the Science corpus: 4 papers; trusts 42 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 41 citations into it; #5,562 of 12,932 by trust here, #4,014 by citations
• Artificial Intelligence — 32 citations into it; #13,452 of 35,345 by trust here, #13,353 by citations
• Computer Vision and Pattern Recognition — 15 citations into it; #8,793 of 21,575 by trust here, #8,952 by citations
• Statistical Learning Theory — 15 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Molecular Biology — 12 citations into it
• Information Systems — 10 citations into it; #7,092 of 8,771 by trust here, #6,770 by citations
• Control and Systems Engineering — 7 citations into it

Whom Christine Tuleau-Malot trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Leo Breiman
2. Trevor J. Hastie
3. Jason Aaron Edward Weston
4. Jianqing Fan
5. Isabelle M Guyon
6. Niko Speybroeck
7. Luc Devroye
8. Bernard Walter Silverman
9. Mats Rudemo
10. U. Groemping

Who trusts Christine Tuleau-Malot overall

1. Hristos Tyralis
2. Jonathan Brophy
3. Maximilian Pichler

Papers from Christine Tuleau-Malot's perspective

Ordered by how strongly the researchers Christine Tuleau-Malot trusts endorse each paper. Same corpus, a different order for every researcher.

1. Random Forests
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Regression Shrinkage and Selection via the Lasso
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Pattern Recognition and Machine Learning

Their papers

• Variable selection using random forests (2010) — 1,812 citations
• VSURF: An R Package for Variable Selection Using Random Forests (2015) — 550 citations
• Random Forests for Big Data (2015) — 357 citations
• Adaptive density estimation: a curse of support? ✩ (2009) — 62 citations